I hypothesize that learning a vocabulary to communicate between components of a system is equivalent to general learning. Moreover, I assert that some problems of general learning, such as eliminating bad hypotheses, deepening shallow representations, and generation of near-misses, will become simpler when refactored into communication learning problems.

Subjects: 2. Architectures; 7. Distributed AI

Submitted: Mar 24, 2005

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